Energy-Aware Coverage Planning for Heterogeneous Multi-Robot System

TL;DR

This paper introduces a distributed, energy-aware coverage control law for heterogeneous multi-robot systems that accounts for varying energy capacities and depletion rates, improving coverage efficiency.

Contribution

It proposes a novel Lloyd's algorithm-based controller that dynamically adjusts robot weights based on energy characteristics, addressing a gap in existing energy-aware coverage methods.

Findings

The controller effectively balances energy consumption and coverage performance.

Simulations and real-world tests validate improved efficiency over baseline methods.

The approach adapts to diverse energy profiles in heterogeneous robot teams.

Abstract

We propose a distributed control law for a heterogeneous multi-robot coverage problem, where the robots could have different energy characteristics, such as capacity and depletion rates, due to their varying sizes, speeds, capabilities, and payloads. Existing energy-aware coverage control laws consider capacity differences but assume the battery depletion rate to be the same for all robots. In realistic scenarios, however, some robots can consume energy much faster than other robots; for instance, UAVs hover at different altitudes, and these changes could be dynamically updated based on their assigned tasks. Robots' energy capacities and depletion rates need to be considered to maximize the performance of a multi-robot system. To this end, we propose a new energy-aware controller based on Lloyd's algorithm to adapt the weights of the robots based on their energy dynamics and divide the area of interest among the robots accordingly. The controller is theoretically analyzed and extensively evaluated through simulations and real-world demonstrations in multiple realistic scenarios and compared with three baseline control laws to validate its performance and efficacy.